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{\bf Abstract of Bachelor Thesis} \\

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{\bf An approach to fast malware classification based on malware's meta-data using machine learning technique}
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  With the rapid increase of malware, it is important for malware analysis to classify unknown malware files into malware families. From that, the behavior and characteristics of malware will be characterized accurately. In this paper, an approach was introduced for perform fast malware classification based on meta-data of malware's file. A machine learning technique, called decision tree algorithm, is used to classify malware rapidly and correctly. Experimental results of the malware samples show that our system successfully determined some semantic malware similarities, especially showed their inner similarities in behavior and static malware characteristic.  \\

Keywords:

Malware, static analysis, decision tree.

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{\bf Pham Van Hung}\\
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{\bf Faculty of Environment and Information Studies}\\
{\bf Keio University}\\
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